基于肿瘤相关成纤维细胞基因构建乳腺癌预后预测模型及免疫浸润分析  

Construction of Prognostic Prediction Model of Breast Cancer Based on Tumor-associated Fibroblast Genes and Analysis of Immune Infiltration

作　　者：孙莉莉 安外尔·约麦尔阿卜拉 刘富中 布尔兰·叶尔肯别克 迪丽娜尔·叶尔夏提 郭文佳[1] SUN Lili;ANWAIER Yuemaieraboa;LIU Fuzhong;BUERLAN Yeerkenbieke;DILINAER Ye;GUO Wenjia(Affiliated Cancer Hospital of Xinjiang Medical University,Urumqi 830011,China)

机构地区：[1]新疆医科大学附属肿瘤医院,乌鲁木齐830011

出　　处：《生物技术进展》2024年第2期312-322,共11页Current Biotechnology

基　　金：新疆维吾尔自治区自然科学基金杰出青年科学基金项目(2022D01E27);新疆维吾尔自治区天池英才项目(2022TCYCGWJ)。

摘　　要：乳腺癌的转移和恶性进展与肿瘤微环境密切相关。肿瘤相关成纤维细胞(cancerassociatedfibroblasts,CAFs)是肿瘤微环境中比较重要的细胞,可影响肿瘤的进展及治疗。从基因表达综合数据库获得乳腺癌单细胞测序数据,对肿瘤微环境细胞进行分簇,再利用WGCNA识别CAF相关的关键基因,用该基因在TCGA-BRCA数据库中构建风险评分模型,进行生存分析、Cox回归分析、ROC曲线、构建列线图预测模型性能;通过GO和KEGG分析模型相关通路;利用体细胞突变、免疫浸润分析、干性指数分析以及药物敏感性分析探讨风险评分与临床特征及肿瘤微环境的关系。研究构建了基于10个CAF基因的乳腺癌预后预测模型,根据风险评分将患者分为高低风险组并进行验证,其中高风险组患者的预后更差,列线图和ROC曲线也显示模型具有良好的预测效能,乳腺癌病人免疫浸润水平更低、干性指数更高,且高风险组病人对紫杉醇及拉帕替尼这2种药物的敏感性更高。结果表明,10个CAF相关基因的风险评分可独立预测乳腺癌的预后及治疗效果,为明确CAF相关基因在乳腺癌中的作用机制提供了思路,也为乳腺癌易感基因患者的临床个体化治疗提供了理论依据。Metastasis and malignant progression of breast cancer are deeply related to the tumor microenvironment.Tumor-associ‐ated fibroblasts(CAFs)are comparatively important cells in the tumor microenvironment which have implications on tumor pro‐gression and treatment.We obtained single-cell sequencing data of breast cancer downloaded from gene expression omnibus data‐base,clustered the cells of tumor microenvironment,and then used WGCNA to identify the key genes related to CAF,and con‐structed a risk score model with the genes in TCGA-BRCA database,and performed survival analysis,Cox regression analysis,ROC curves,and constructed a column line graph to predict the performance of the model.Model-related pathways were analyzed by GO and KEGG.The relationship between risk score and clinical features and tumor microenvironment was explored by somatic mutation,immune infiltration analysis,stemness index analysis,and drug sensitivity analysis.A prognostic prediction model based on 10 CAF genes was constructed and validated in accordance with the risk scores.Patients were classified into high-and low-risk groups according to the risk scores,and the prognosis of patients in the high-risk group was worse,and the column plot and ROC curve also showed that the model had a good predictive efficiency,and the immune infiltration level of patients with breast cancer in the high-risk group was lower and the stemness index was higher,and the patients in the high-risk group were more sensitive to 2 drugs,namely,paclitaxel and lapatinib.Patients in the high-risk group had a lower level of immune infiltra‐tion and a higher dryness index,and patients in the high-risk group had a higher sensitivity to paclitaxel and lapatinib.The risk scores of the 10 CAF-related genes can individually predict the progress and therapeutic effects of breast cancer,which provides ideas for clarifying the mechanism of the role of CAF-related genes in breast cancer and provides a theoretical basis for the clini‐cal individualization of treatment for

关 键 词：乳腺癌 肿瘤相关成纤维细胞 肿瘤突变负荷 预后模型 免疫浸润 

分 类 号：Q75[生物学—分子生物学] R737.9[医药卫生—肿瘤]